Shifting from extensive to intensive agricultural systems: a case study in the Sudan

Agricultural Systems, Vol. 58, No. 2, pp. 253±268, 1998 # 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain PII: S0308-521X(98)00053-5 0308-521X/98 $19.00+0.00

Shifting from Extensive to Intensive Agricultural Systems: A Case Study in the Sudan Mohamed M. Ahmed & John H. Sanders* Department of Agricultural Economics, Purdue University, 1145 Krannert Building, #609, West Lafayette, IN 47907-1145, USA (Received 24 February 1998; revised version received 1 June 1998; accepted 8 June 1998)

ABSTRACT The development of the mechanized vertisols of Sudan has been very successful in achieving rapid expansion of crop area. Unfortunately, there has been minimal use of purchased inputs. Hence, crop yields have been low and declining over time with increasing variability of output. Now the frontier is disappearing and past land and credit subsidies have been eliminated. With modeling, we show that in the absence of the area-expansion option, even riskaverse farmers shift to the more intensive technologies involving improved cultivars and fertilization. We explore several options involving further research or policy changes that would induce intensi®cation even before the passing of the frontier. # 1998 Elsevier Science Ltd. All rights reserved

INTRODUCTION The development of mechanized farming on the vertisols of Sudan is an outstanding success in terms of rapid expansion of crop area and output. This region presently produces most of the country's principal staple, sorghum. Unfortunately, crop yields have been low and declining over time with increasing variability of output. As area expansion is becoming more dicult with falling yields and increasing transportation costs, the need to shift from extensive to intensive systems is recognized by both policymakers and researchers. *To whom correspondence should be addressed. Fax: +1-765-494-9176; e-mail: sanders@ agecon.purdue.edu 253

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We analyze factors in¯uencing the area-expansion phase and estimate the pro®tability and sustainability of the future introduction of intensive technologies in the semiarid vertisols of Sudan. Our analysis is based on simulation and whole-farm modeling of farms where soils have already been depleted and for farmers just moving onto virgin soils. We hypothesize that (1) the reliance on extensive systems was encouraged by the economic policy distortions, and (2) now that these distortions have been removed, the lack of access to new land will encourage the shift to intensive technologies. We also consider research and policy that could foster the intensi®cation process even before the frontier has been eliminated. In the ®rst two sections, we review the history of mechanized farming on the vertisols and report on the area and yield trends plus expected yields over time for potential new intensive technologies. In the next three sections we describe the economic model and data used and present results of the simulation and programming, emphasizing the roles of the land-supply situation and research/policy shifts. Finally, we draw conclusions and consider implications. MECHANIZED FARMING IN SUDAN Sorghum is the principal staple for the majority of Sudan's population. It is produced in all three of the country's crop-production systems: (1) irrigated; (2) traditional small-scale, rainfed sector; and (3) large-scale, commercial mechanized farming (Sanders et al., 1996). This last sector is located in the Central Clay Plains between isohyets 400 and 800 mm of rainfall (Fig. 1). The mechanized sector produces approximately three times the quantity of sorghum of each of the two other sectors. Except for adverse weather years, sorghum from the mechanized drylands was 55±75% of total country output during the 1980s and 1990s. The mechanized farming sector has experienced a rapid expansion of crop area and output, especially during the last two decades. The area in mechanized sorghum production increased from 1.3 million ha in 1976 to 3.8 million ha in 1996, down from 5 million ha in 1993 and 1995 (Fig. 2). Mechanized farming in Sudan began in the mid-1940s on the vertisols of Gedaref in eastern Sudan. Settlement on these plains had been restricted by the lack of available drinking water and the diculty of land preparation without mechanization. In 1953 with the failure of state-managed farms, the government introduced private leases of 420 ha farms at a nominal land rent. Since then, mechanized farming has spread to other areas in central, western, and southern Sudan. In the late 1980s, approximately 5000 entrepreneurs operated these farms with 100,000 wage-earning employees and up to a million seasonal laborers

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Fig. 1. Mechanized sectors in Sudan. Source: Adapted from Sanders et al. (1996, p. 116).

for 2 months of weeding and harvesting (Holdcroft, 1989, p. 5). Seasonal labor is contracted for land clearing, weeding, and harvesting. Tillage, planting, and threshing are done mechanically with the use of tractors. Weeding and harvesting are the bottleneck periods for hired labor. In the mechanized rainfed zone, there is sesame, cotton, and millet production, but during 1980±96, around 87% of the crop area was in sorghum. Most of the farms are 630 ha (the expanded minimum size grant), but some of the old farms in the eastern regions, where mechanized farming began, are 420 ha (Ahmed, 1994). The heavy vertisols of the mechanized rainfed area are dicult to work and are characterized by low organic matter and little nitrogen content. Nevertheless, as there is no de®ciency of other plant nutrients, the soils are moderately fertile (Kevie and Burayma, 1976). Their cracking characteristics give them some water-retention capacity when dry, but they seal when wet (Bein, 1980, p. 122; Dudal and Eswaran, 1988, pp. 9, 10, 13, 21).

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Fig. 2. Sorghum area and production (1964±96) in the mechanized sector of Sudan. Source: 1964±93 data from Sanders et al. (1996, p. 115); 1994±96 data from Nichola and Sanders (1996, p. 110).

The cropping season begins in late June and July after the ®rst rains when the soil is softened and weeds germinate. Plowing and planting need to be done early and quickly to capture the early rains. Two weeding operations are then done manually. No fertilization or other chemicals are used. Among the sorghum cultivars grown in the mechanized area, many were introduced in the early 1970s as combinable high-yielding cultivars (for example, Dabar 1 and Gadam Elhamam 47; Nichola and Sanders, 1996). In the 1990s, with emphasis on Striga resistance, three new cultivars were introduced (SRN 39, IS 9830 and M 90393) with some di€usion being reported (ICRISAT, unpublished data). Although these cultivars are openpollinated, the major constraint to adoption of the new cultivars has been the unavailability of quality seeds (Ahmed, 1994). RAPID CROP-AREA EXPANSION To encourage private investment in mechanized farming on the vertisols, the government allocated substantial public investment for the mechanizedsector infrastructure, research, and services. Land, machinery, fuel, and credit were provided at subsidized prices. At the same time, foreign exchange and pricing policies resulted in a bias against agricultural tradables, including sorghum, thereby reducing the pro®tability of mechanized farming (D'Silva and Elbadawi, 1988, p. 431). The area in mechanized sorghum reached almost a million ha by 1964. From 1964 to 1980, the sorghum area in the mechanized rainfed sector increased slowly at a rate of 1% per annum (Table 1). Hence, input subsidies

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TABLE 1 Time Trends of Area, Yield, and Production of Mechanized Sorghum in Sudan (% Per Year) Period 1964±80 1981±96

Area

Yield

Production

1.0a,c (2.5) 2.7a,c (3.7)

ÿ1.0a (3.5) ÿ1.0b (1.2)

0.0c,b (0) 1.8c,b (1.2)

Rates reported are the slope coecients of exponential growth equations estimated from time series data for the period given. For signi®cance of the di€erence between the two periods, a regression for the entire periods was estimated with a dummy variable for the latter period. Figures in parentheses are t-values. a Signi®cant at 5% probability level. b Not signi®cant at 5% probability level. c Signi®cant di€erence between ®rst and second periods.

appear to have only partially o€set the macroeconomic biases that reduced the pro®tability of cereal production. In the early 1980s, the pro®tability of sorghum production increased with devaluations and the elimination of direct and indirect taxes on agriculture. The expansion in sorghum area accelerated to 2.7% per year from 1981 to 1996. Both the number of farms and the area of individual farms increased over this period. Production increased 1.7% per year, but with extreme variability (Fig. 2) as sorghum yields continued to decline at the same rate experienced during the 1960s and 1970s (1%). In the early 1990s, further market liberalization and privatization policies followed and input subsidies were completely eliminated. Policy objectives were to reduce food imports (mainly wheat) and to increase the domestic production of staples. Domestic sorghum prices increased and the private incentives for mechanized farmers improved substantially. There is a debate in the Sudan about whether yields on the mechanized vertisols have been declining. Some argue that with the occasional fallows and the churning characteristic of vertisols bringing nutrients from lower levels to levels accessible to crops, fertility reduction over time may not be a problem. For empirical observation, declining trends at the aggregate level are dicult to observe because of the enormous between-year yield variability of rainfall and other exogenous shocks. To estimate the trends at the farm level, sorghum yields on the vertisols were simulated, using the Environmental Policy Integrated Climate (EPIC) model (see Appendix for details). EPIC combines soil, water, and crop modeling to give yield estimates over time plus the e€ects of alternative cropping activities on the major soil parameters (Sanders et al., 1995: Lee et al., 1997). Detailed soil, weather, and management data were obtained from the Sudan.

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When the farmers' traditional practice of continuous sorghum without fertilizers was modeled forcing constant normal rainfall to eliminate this climatic stochastic variation, the model results clearly showed the long-run yield decline (Fig. 3). In practice many farmers have an occasional fallow year since low prices or other factors result in a decision not to plant or poor expected yields or prices result in their not harvesting. Since there was no systematic fallowing pattern here and most farmers would plant and harvest continuous sorghum for most of the ®rst decade after settlement, this occasional fallow was not modeled and only expected to slow down this yield decline process of approximately 60% of initial levels after 16 years. Comparing these simulated yields without weather e€ects with the aggregate yield data from the mechanized sector clearly indicates the declining yield trend (Fig. 3). Observed farm yields during the 1980s and 1990s averaged 500 kg/ha, 40% lower than in the 1964±80 period. A principal factor behind this decline in yields is the soil-mining e€ect of extensive cropping systems without application of fertility-improving inputs. Surveys in 38 Sub-Saharan African countries indicated that agricultural uses of land resulted in mean net nutrient removals from the soil of 22 kg of nitrogen, 6 kg of phosphorus, and 23 kg of potassium per hectare per year (Crosson and Anderson, 1994). With these low and declining yields, area expansion is obviously not a sustainable long-run strategy to maintain food production. Are there potential technologies to increase yields on the rainfed vertisols? The principal constraint to output increase on the vertisols has been declining soil fertility and the use of traditional cultivars. Combining inorganic fertilizers and improved cultivars is hypothesized to substantially improve crop yields on the vertisols. Several new, high-yielding cultivars have been

Fig. 3. Aggregate and simulated sorghum yields on a mechanized farm in eastern Sudan (1964±96). Source: Adapted from Sanders et al. (1996, p. 119); aggregate yield data for 1993± 96 from Nichola and Sanders (1996, p. 110).

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developed (HD-1, SRN 39) and soil-fertility research has been undertaken over several decades (Ahmed, 1994). With a simulation model, the long-run e€ects of various combinations of seed/fertilizer technologies on the mechanized rainfed area were evaluated. To evaluate the e€ect of a new cultivar, data from regional trials were utilized. Generally, these trials were fertilized so it was necessary to adjust the data to delete the fertilizer e€ect. In the simulation, the initial yield advantage disappears as nitrogen de®ciencies became more serious. According to EPIC runs here, introducing only a new cultivar would increase yields approximately 13% over a 16-year period, with increasing soil-fertility de®cits resulting in declining yields for the new cultivar (Fig. 4). Continuous cropping of either new or traditional cultivars of sorghum without fertilization for 16 years depleted about 48% of the soil-available nitrogen. Combining the new cultivar with 47 kg/ha of urea increased yields 58% over the improved cultivar and 600 kg/ha over traditional cultivars. Doubling the fertilizer levels increased yields 30% above the lower fertilizer level, approximately doubling yields of the traditional cultivars. With the lower fertilization rate, the minimum yield obtained was in excess of 1.2 t/ha.

Fig. 4. Simulated sorghum yields of actual and potential technologies in the mechanized rainfed zone with the historic weather conditions, 1973±88. Note: 1 N denotes application of 94 kg/ha urea and 0.5 N is 47 kg/ha urea. Sorghum yields of all technology alternatives in each state-of-nature were simulated using EPIC. Physical and chemical properties of the typical soil pro®le under permanent fallow in the vertisols of eastern Sudan were documented by Kevie and Burayma (1976) and used in the simulation. Daily and monthly weather variables, including minimum and maximum temperature and rainfall for the 1973±88 simulation period, were used. The model is validated using a time series of sorghum yields in eastern Sudan for 1973±88. For detailed description of data used and validation results, see Ahmed (1994). Source: Sanders et al. (1996, p. 130).

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Yields did not decline even after 16 years of cropping. Hence, these yield increases are sustainable over the period studied in contrast with traditional or new cultivars alone. Yields simulated here do not re¯ect the e€ects over time of biotic factors, such as increased Striga, insects, and disease. Nutrients other than nitrogen and phosphorus would ultimately become limiting, so this is only a ®rst approximation of the requirements for sustainable continuous sorghum yield increases. Nevertheless, these are respectable yield increases from low to moderate fertilization in an area where sorghum yields are 500±700 kg/ha. Relative responses to fertilization were higher but the initial yields lower on exhausted soils as compared with virgin land. For example, the application of 94 kg/ha of urea doubled sorghum yields of the improved variety on exhausted land compared to only a 73% yield increase on virgin land (Table 2). Besides soil fertility, the other dominant constraint in semiarid regions is the availability of sucient water at the critical times for plant development. A water-retention activity was introducedÐtied ridges combined with fertilization, since more water increases the return and reduces the riskiness of fertilization. Tied ridges increased expected yields only 6% (Fig. 4). There was a positive response to tied ridges in only 7 of the 16 years simulated. In some years, there was excess water when rainfall was high for these heavy, cracking soils. To summarize, the intensive technologies simulated here improved sorghum yields substantially. Following continuous cropping, with yields of both traditional and improved cultivars falling to low levels, extensive technologies are not sustainable long-run strategies. Will risk-averse farmers ®nd it pro®table to adopt these new technologies on virgin lands and on depleted farms? A programming model is used to respond to this question. TABLE 2 Average Sorghum Yields (t/ha) with Alternative Fertilization on Two Types of Soils in Eastern Sudan Technology Traditional cultivar Improved cultivar Improved cultivar+0.5 Nb Improved cultivar+0.5 N+tied ridging Improved cultivar+1 N Improved cultivar+1 N+tied ridging

Virgin soils

Exhausted soils a

0.81 0.91 1.42 1.48 1.67 1.76

0.62 0.76 1.18 1.24 1.51 1.52

Average sesame yield was 0.21 t/ha on virgin soil and 0.16 t/ha on depleted soil, from ®eld observations (Ahmed, 1994). Source: Ahmed (1994). a Exhausted soil is de®ned as soil subjected to continuous cropping for 12 years. b 1 N=94 kg/ha urea; 0.5 N=47 kg/ha of urea.

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MODEL AND DATA In the farm model, the farmer maximizes the expected value of a power utility function subject to resource constraints (land, labor, machinery, and capital). The utility function is: uˆ

w…1ÿ† 1ÿ

where u is utility of income, w is net income and  is the relative risk aversion coecient. This utility function exhibits decreasing absolute risk aversion and constant relative risk aversion. The relationship between risk aversion and wealth can be explained intuitively using the concept of the risk premium. A risk premium is the amount of money a decision-maker is willing to pay to avoid a risky prospect. Decreasing absolute risk aversion implies that the risk premium a decision-maker is willing to pay decreases with increasing wealth or he needs less insurance as wealth increases. A constant relative risk aversion means the risk premium as a proportion of wealth remains constant as wealth increases. Since it is easier to take risk at a higher levels of wealth or income, most people will be decreasingly averse to risk if they grow richer (Hardaker et al., 1997, p. 98). Hence, this seems a reasonable speci®cation for the utility function. Risk-aversion coecients were not elicited from farmers but sensitivity analysis for a wide range of risk aversion was undertaken in the results. There is yield variabilityÐhence riskÐassociated with climate, insects, and diseases but only the climatic variation is captured in the simulation. The state of biological knowledge is insucient to incorporate these two biotic factors (insects and disease) in the simulation. The model includes two crop activities (sorghum and sesame) in addition to fallow. Sorghum is produced with one or more of seven technologies: (1) fallow, (2) traditional cultivar, (3) new cultivar, (4) new cultivar with low fertilization (47 kg/ha urea), (5) new cultivar with low fertilization and tied ridging; (6) new cultivar and moderate fertilization (94 kg/ha urea); and (7) new cultivar, moderate fertilization, and tied ridging. Crop yields for a typical farm on the vertisols for each technology were simulated using EPIC (Ahmed, 1994). The farm programming model consists of 16 states-of-nature obtained from the historical rainfall data over the period 1973±88. The probability of each was considered equally likely, and the combined 16 rainfall events were considered to represent all possible climatic occurrences. Two sets of yield distributions were simulated, one for the virgin soils and one for the depleted soils after 12 years of continuous sorghum. A future extension of the model would introduce price variability but only a mean price was utilized here.

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The model includes constraints for hired labor for each operation (land preparation, planting, ®rst and second weeding, crop cutting, and threshing). Labor constraints were de®ned on operations, rather than time periods, to re¯ect the ¯exibility of adjusting the timing of the operation according to rainfall. The average farm area is 630 ha, but the farmer can rent additional land or acquire new land at the prevailing market price and hire labor at the current rates with no restrictions. The supply of machinery hours at planting time is determined by the average machinery stock available in the Gedaref region but farmers can also buy or sell machinery services. Total operating capital available is the maximum equity expenditure on the average farm in the Gedaref region (Ahmed, 1994). Similarly, equity capital can be augmented with credit at the market interest rate of 30%. Validating the model Initial simulations with the historic land and credit subsidies and availability of land for expansion were used to validate the farm model. The results indicate that the pro®t-maximizing scenarios deviated substantially from the observed cropping plans on the vertisols of eastern Sudan (Table 3). The representative farm on the vertisols of eastern Sudan cultivates 793 ha including 163 ha of rented land with sorghum grown on 700 ha without fertilizer application and sesame grown on 93 ha, according to farm surveys in the area. Increasing relative risk aversion in the model to a coecient of 2 considerably lowers crop areas in both sorghum and sesame and is approximately equal to average area observed.

TABLE 3 Farm-Programming Model Results with Historic Subsidies and Availability of Land for Expansion on Virgin Soils Crop activity

Improved sorghum Sesame Total crop area Rented area

Farm observations a (ha) 700.0 93.0 793.0 93.0

Results b (ha) 0.0c

1.5c

2.0c

749.3 288.1 1037.4 407.4

653.1 264.2 917.2 287.2

578.9 111.4 690.3 60.3

Source: Ahmed (1994). Survey results in eastern Sudan. b Model results on virgin soils with historic subsidies. Farmers were allowed to rent additional land at market prices. In absence of improved varieties, the model selects traditional cultivars instead of improved sorghum. Model results indicate it is unpro®table to crop depleted land. c Relative risk-aversion coecients. a

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Mechanized farming is apparently associated with a high level of risk as a result of erratic rainfall and price ¯uctuations. It was gratifying that the model selected the new cultivars because that is the only new technology consistently observed being adopted in the region. Neither fertilization activity was ever chosen. Nor is fertilization observed in the region. IMPACT OF PREVIOUS ECONOMIC POLICY Did historic economic policies encourage the extensive systems utilized on the vertisols? To accelerate settlement on the frontier, farmers paid only a nominal land tax for tracts of 630 ha. Credit was provided at subsidized interest rates and machinery-import costs were reduced by the overvalued exchange rate. Institutional land rents charged by the government increased from US$0.29/ha in 1989 to US$0.70/ha in 1991 (Habash, 1990; Salih, 1993). This change was used in the model. The market rental rate presently is US$1.75/ha, which is still very low. In contrast to the subsidized interest rate (12%), farmers now rely on the commercial lending institutions for credit at the prevailing cost (30%). Applying the historic conditions for virgin land in the modeling, a vertisol farmer maximizes expected utility by expanding his crop area by 60±407 ha rather than adopting yield-increasing technologies (Table 3). Most farm area is allocated to improved sorghum cultivars and the rest to sesame. Both newcultivar adoption and the absence of fertilization are consistent with observed farmer behavior in the region. Eliminating subsidies on land and credit has a minimal e€ect on crop choices on the virgin soils, slightly reducing the sorghum and total crop area (Ahmed, 1994). On the depleted soils with or without the subsidies, it is unpro®table to cultivate these soils and the farmer just moves on into the new area. Although the cost of area expansion is more than doubled in the model by removing the subsidies, extensive production is still pro®table on virgin soils without shifting to the more intensive fertilizer technologies. This is because the cost of bringing additional units of land under extensive production using the available farm resources is still low, the additional costs of fertilizer are high, and the yield increase from fertilizer application on virgin land is relatively small. After Sudan removed macro-policy disincentives for producing sorghum with several devaluations and allowed sorghum exports, high sorghum prices made the area expansion very pro®table. Average real sorghum prices were 50% higher during the 1980s than in the 1970s (Ahmed, 1994). In the modeling, even in the absence of subsidies on land and credit, farmers on the virgin lands had minimal incentives to introduce more intensive technologies

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and farmers on depleted lands shifted entirely to new land while they continued to pay land taxes on these depleted farms. This is exactly what farmers in the region have been observed doing. DISAPPEARANCE OF THE FRONTIER What happens when the frontier disappears? To model this shift, we did not allow land rental. Even at the higher risk-aversion level, the farmer on the virgin soils utilizes the low fertilization level on one-fourth of the sorghum area (Table 4). Tied ridges are eliminated as risk aversion is increased since tied ridging can become risky on the vertisols due to the excess water problem in a higher-rainfall season. The e€ect of the disappearance of the frontier on the adoption of intensive technology on depleted soils is more dramatic. Here risk-indi€erent farmers allocate all their sorghum area (478 ha or 76% of crop area) to the improved variety with the high level of fertilization, according to model results. Increased risk aversion reduces the total crop area but does not a€ect the intensity of production. When the frontier was still open, farmers left this soil idle and moved to new regions. With the disappearance of the frontier, use of fertilizers makes recovery of the nutrient-depleted zone possible. TABLE 4 Adoption of Intensive Technologies on the Vertisols With and Without Land-Supply Restriction and Policy Changes Technology

Historic policy and unrestricted land supply Virgin land

Improved sorghum Improved sorghum+0.5 Nb Improved sorghum+0.5 N +tied ridging Improved sorghum+1 N Sesame Total crop area Rented area

Restricted land supply Virgin land

Depleted soil

Risk neutral

Risk averse a

749.3 0.0 0.0

578.9 0.0 0.0

235.4 150.8 132.4

430.7 126.6 0.0

0.0 0.0 0.0

0.0 0.0 0.0

0. 0 288.2 1037.4 407.4

0.0 111.4 690.4 60.4

0.0 111.4 630.0 N/A

0.0 72.4 630.0 N/A

478.1 158.2 630.0 N/A

402.0 65.1 467.1 N/A

Risk Risk Risk Risk neutral averse a neutral averse a

Source: Ahmed (1994). N/A, land is no longer available for expansion. Risk-aversion simulation is represented by a relative risk-aversion coecient of 2, at which the model approximates the observed cropping plan. All area is in hectares. b 1 N denotes application of 94 kg/ha urea and 0.5 N is 47 kg/ha urea. a

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The degree of intensi®cation depends upon the initial soil fertility since this determines the relative response to fertilizer application. On virgin soils, the farmer has the opportunity to exploit the natural fertility; hence, only part of the sorghum area is fertilized. In contrast, on the depleted soils, moderatelevel fertilization and the new cultivar are used on the whole area. Most of the cropland of the vertisols has been in the traditional continuous cropping (with occasional short periods of fallow) for a decade or more. The introduction of the more intensive technology can then restore the productivity of these areas and allow sustainable land use. This reduces the need to open new areas for mechanized food production. Is it necessary to wait until the frontier is gone to begin the intensi®cation process? Policy and research activities are evaluated that would encourage farmers on virgin soils to begin supplying some of the nutrients rather than mining the soils even when they still have the option to rent. A fertilizer price subsidy of 25% is needed for adoption of 47 kg/ha of urea on the entire sorghum area on the virgin farm with the rental option (Table 4). This fertilizer subsidy is unlikely, given the present course of economic and agricultural policy away from these types of subsidies. Rather, researchers could develop agronomic practices that would increase sorghum response to fertilizer application. A 20% increase in the expected yield of the improved sorghum from application of 94 kg/ha of urea on virgin soils (from 1.62 to 1.94 t/ha) is sucient for the intensive technology to be adopted even while farmers can expand the area cultivated. A similar increase in expected yield of the improved variety with 47 kg/ha of urea from 1.42 to 1.7 t/ha leads to adoption. These are moderate yield increases and are expected to be feasible for researchers developing more responsive cultivars and improving fertilization techniques. CONCLUSIONS The extensive practice of continuous cropping without fertilizer application is a short-run strategy encouraged by easy access to land at low cost. In the long run, yields decline as a result of nutrient depletion; hence, farming of such depleted areas becomes unpro®table. Apparently the availability of the frontier for expansion of activities was a predominant factor encouraging an extensive development process. Area expansion occurred much more rapidly in periods of higher sorghum prices, as after 1980. So the historical input subsidies were primarily an income transfer or increased rent for large farmers on the vertisols as the modeling indicated minimal area reduction resulting from substantial reduction of the subsidies on land and credit.

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Once there is no longer an opportunity to acquire more land on the rental market, the optimum crop choice on both the depleted and the virgin soils is to intensify production. On the depleted soils, the fertilized area is larger and the levels of fertilization greater. But on virgin land, even risk-averse farmers use a low level of fertilization on much of the crop area. Putting a subsidy on the fertilizer price or increasing the yield responsiveness of sorghum cultivars to fertilizers on these soils could introduce the intensi®cation process before the frontier is gone. An especially important activity for the national agricultural research organization (the Agricultural Research Corporation) is to continue this research on the intensi®cation process. Public investment in input and output marketing infrastructure could ensure that fertilizer is available and that the farmer can get his product rapidly and cheaply to urban markets. In other Sub-Saharan countries, new lands are opening as, for example, where the control of onchocerciasis (river blindness) has been successful. Development strategies in these areas need to focus on policies to encourage intensi®cation rather than merely on crop-area expansion. Research to adapt and improve the intensi®cation option would encourage an earlier emphasis on getting yields up rather than expanding crop area. The shift to intensive technologies depends on the soil-fertility and management practices. Both factors change over time and are in¯uenced by current management of the soil resource. Future research should incorporate dynamic aspects of the shift to intensive technologies and long-run, soilmanagement strategies and should evaluate optimal adjustments to sustainable land use over time. ACKNOWLEDGEMENTS For critical comments and suggestions, we are grateful to Timothy G. Baker of the Department of Agricultural Economics, Purdue University, and a reviewer for this journal. Figures 1 to 4 were adapted or taken from The Economics of Agricultural Technology in Semiarid Sub-Saharan Africa, by John H. Sanders, Barry I. Shapiro and Sunder Ramaswamy # 1996, pp. 115, 116, 119 and 130 and are reprinted with permission from The John Hopkins Unversity Press. REFERENCES Ahmed, M. (1994) Introducing new technologies on the vertisols of eastern Sudan. PhD thesis, Purdue University, West Lafayette, IN. Bein, F. L. (1980) Response to drought in the Sahel. Journal of Soil and Water Conservation 35(3), 121±124. Crosson, P. and Anderson, N. (1994) Achieving a sustainable agricultural system in

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Sub-Saharan Africa, Paper No. 7, Post-UNCED Series, Building Blocks for Africa 2025. World Bank, Washington, DC. D'Silva, B. and Elbadawi, I. (1988) Indirect and direct taxation of agriculture in Sudan: the role of the government in agricultural surplus extraction. American Journal of Agricultural Economics 72(2), 431±436. Dudal, R. and Eswaran, H. (1988) Distribution and classi®cation of the vertisols. In Vertisols: Their Distribution Properties, Classi®cation and Management, eds L. P. Wilding and R. Puentes. Texas A&M University Press, College Station, TX, pp. 1±22. Habash, M. K. (1990) Potential returns and constraints to the adoption of new technologies in the mechanized rainfed region (eastern vertisols) of the Sudan. PhD thesis, Purdue University, West Lafayette, IN. Hardaker, J. B., Huirne, R. B. M. and Anderson, J. R. (1997) Coping with Risk in Agriculture. CAP International, New York. Holdcroft, L. E. (1989) The Sudan today: an economy and its agriculture in crisis, Field Sta€ Report 14, 1988±89. USAID/Africa/Middle East, Washington, DC. Kevie, W. Van Der and Burayma, I. M. (1976) Explanatory soil survey of Kassala Province: a study of physiography, soils and agricultural potential, Soil Survey Report No. 73. Soil Survey Administration, Wad Medani, Sudan. Lee, J. G., Southgate, D. D. and Sanders, J. H. (1997) Methods of Economic Assessment of On-Site and O€-Site Costs of Soil Degradation. In Methods for Assessment of Soil Degradation, eds R. Lal, W. H. Blum, C. Valentine and B. A. Stewart, pp. 475±94. CRC Press, Boca Raton, FL. Nichola, T. and Sanders, J. H. (1996) A probit analysis of the determinants of adoption when inputs are rationed: the Gezira experience with hybrid sorghum. Science, Technology, and Development 14(3), 107±119. Salih, A. A. A. (1993) Sustainability and pro®tability of intensive cropping technologies on the dryland vertisols of Sudan: a simulation approach with EPIC. PhD thesis, Purdue University, West Lafayette, IN. Samani, Z., Hargreaves, G. H., Zuniga, E. and Keller, A. A. (1987) Estimating crop yields from simulated daily weather data. Applied Engineering in Agriculture 3(2), 290±294. Sanders, J. H., Southgate, D. D. and Lee, J. G. (1995) The economics of soil degradation: technological change and policy alternatives, SMSS Technical Monograph No. 22. USDA/NRCS, World Soil Resources, Washington, DC. Sanders, J. H., Shapiro, B. I. and Ramaswamy, S. (1996) The Economics of Agricultural Technology in Semiarid Sub-Saharan Africa. Johns Hopkins University Press, Baltimore, MD. Williams, J. R., Dyke, P. T., Fuchs, W. W., Benson, V. W., Rice, D. W. and Taylor, E. D. (1990) EPIC: erosion/productivity impact calculator: 2. User manual, Technical Bulletin No. 1768. US Department of Agriculture, Washington, DC.

APPENDIX Details of EPIC simulations The Environmental Policy Integrated Climate (EPIC) model was developed to evaluate soil, water, and management impacts on long-term productivity.

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It is a substantial improvement for erosion over the Universal Soil Loss Equation and a much further extension to handle crop, soil, and water interactions than the usual crop-simulation models. It was used here to simulate the long-run e€ects of various combinations of seed-fertilizer technologies for sorghum production on the vertisols. EPIC is a multiyear/multicrop growth simulation model and it is very data-intensive. EPIC requires data on minimum and maximum temperature, rainfall, solar radiation, relative humidity, and wind. These values over a 16-year period (1973±88) were generated from monthly rainfall, potential evapotranspiration, and temperature recorded in the Sudanese study area using a daily weather generator, `Wmaker', described by Samani et al. (1987). The simulation period represents a wide range of annual rainfall amounts and distribution ranging from 503 to 999 mm and is assumed to be representative of long-run weather patterns in the area. This model was chosen for its capability to assess the e€ect of management changes on long-term soil productivity and also because it is computationally ecient and convenient to use (Williams et al., 1990). Soil parameters of the typical vertisols of eastern Sudan (Gedaref area), reported by Kevie and Burayma (1976), were used in this study to simulate the long-term yields of sorghum under alternative technology options and the associated e€ects on soil fertility. EPIC was validated by comparing average historical yields of traditional sorghum on farmers' ®elds in the simulation area to the predicted yields for the period of 1973±88. The simulated yields appear to be very close to actual yields. The percentage deviation of simulated yields from actual yields is small and with mean absolute error of 7.9%. Regressing actual yields on the simulated yields, the hypotheses that the estimated intercept of 0.03 is zero and the estimated slope coecient of 0.932 equals 1.0 could not be rejected at a 5% signi®cance level. The validated model was then used to obtain a yield distribution for each of the seven technologies discussed in the Model and Data section. The simulated yield distributions were reported in Fig. 4.